JP6762148B2 - Map generation method, mobile robot and map generation system - Google Patents

Description

The present disclosure relates to a map generation method, a mobile robot and a map generation system.

Robot technology has been developed for the purpose of exploration in an environment that is out of the reach of people and automation of performing human substitution work. In recent years, mobile robots and the like that perform cleaning while moving in the home have been sold, and mobile robots have been introduced into familiar areas of human life. In such a mobile robot, in order to determine the movement route, the mobile robot itself needs to correctly recognize its own position and posture and the surrounding environment.

SLAM (Simultaneus Location And Mapping) technology is known as a technology for estimating a self-position and creating a map. In SLAM technology, a sensor provided in a mobile robot, which is an internal sensor for detecting the amount of change in position and posture, and a sensor provided in the mobile robot, which is an external sensor for capturing relative information with respect to the surrounding environment, are used. In SLAM technology, by using these sensors, it is possible to create a map of the surrounding area together with the estimation of its own position and posture without giving map information to the mobile robot in advance.

The SLAM technology mainly repeats two processes. The first process predicts the current position and posture of the mobile robot from the information acquired by the internal sensor, and is relative to the surrounding environment of the mobile robot based on the predicted position and posture and the map information created in the past. Predict information. In the second process, the likelihood is calculated based on the relative information predicted by the first process and the relative information with respect to the actual surrounding environment obtained by the external sensor. The weights of the reliability of the inner world sensor and the outer world sensor are determined from the calculated likelihood, and the current self-position and posture of the mobile robot and the map information are updated.

Further, Patent Document 1 is disclosed as a method for realizing autonomous movement in an environment where there is a map change. The autonomous driving vehicle disclosed in Patent Document 1 calculates whether or not the autonomous driving vehicle itself can travel by estimating its own position and posture with respect to an object using a sensor such as a laser beam or a camera. .. Then, the autonomous driving vehicle disclosed in Patent Document 1 determines whether or not the autonomous driving vehicle can travel based on the calculated travelability of the autonomous driving vehicle itself and the travelability acquired by the flying object.

Japanese Unexamined Patent Publication No. 2011-108084

Mobile robots that perform exploration and human substitution work are required to generate more accurate maps in addition to determining whether or not they can travel. However, in the autonomous driving vehicle disclosed in Patent Document 1, the point of generating a map with higher accuracy has not been studied.

The present disclosure provides a map generation method, a mobile robot, and a map generation system capable of generating a map with higher accuracy.

The map generation method of the first aspect according to the present disclosure is a map generation method performed by a first mobile robot that moves in a first region and includes a first sensor and a second sensor, and the first information from the first sensor. The first information includes information indicating the amount of movement of the first mobile robot, the second information is acquired from the second sensor, and the second information exists in the observation area of the first mobile robot. The third information is acquired from the third sensor installed in the first area, including the information indicating the distance from the first object to the first mobile robot, and the third information is the observation area of the third sensor. The fourth information indicating the second region, which is the detection region of the second sensor, calculated based on the first information and the second information, including the video information in the above, is acquired, and based on the third information. The calculated fifth information indicating the third region, which is the detection region of the third sensor, is acquired, and the second region and the third region overlap each other based on the fourth information and the fifth information. It is determined whether or not the fourth region, which is a region, exists, and when it is determined that the fourth region exists, the fifth region including the first object in the fourth region is subjected to the first mobile robot. The map information of the first area stored in advance is updated.

The map generation method of the second aspect according to the present disclosure is a map generation method performed by a first mobile robot that moves in a first region and includes a first sensor and a second sensor, and the first information from the first sensor. The first information includes information indicating the amount of movement of the first mobile robot, the second information is acquired from the second sensor, and the second information exists in the observation area of the first mobile robot. The third information is acquired from the third sensor installed in the first area, including the information indicating the distance from the first object to the first mobile robot, and the third information is the observation area of the third sensor. The fourth information indicating the second region, which is the detection region of the second sensor, calculated based on the first information and the second information, including the video information in the above, is acquired, and the calculation is performed based on the three information. The fifth information indicating the third region, which is the detection region of the third sensor, is acquired, and the fourth information, the fifth information, and the map information of the first region stored in advance in the first mobile robot are obtained. Based on the above, it is determined whether or not the second object outside the second region and existing in the fourth region included in the third region has changed from the first position to the second position, and the second object is When it is determined that the position has changed from the first position to the second position, the map information of the first area is updated for the fourth area.

According to the present disclosure, it is possible to generate a map with higher accuracy.

FIG. 1 is a schematic configuration diagram of a map generation system according to the first embodiment of the present disclosure. FIG. 2 is a block diagram showing a configuration of a mobile robot according to the first embodiment of the present disclosure. FIG. 3 is an explanatory diagram of the definition of variance. FIG. 4 is a block diagram showing a configuration of an environmental sensor according to the first embodiment of the present disclosure. FIG. 5 is a diagram showing an example of the operation of the mobile robot and the environmental sensor according to the first embodiment of the present disclosure. FIG. 6 is a flowchart showing a map generation method according to the first embodiment of the present disclosure. FIG. 7A is a diagram showing an example of the operation of the mobile robot and the environmental sensor according to the first embodiment of the present disclosure. FIG. 7B is a diagram showing an example of the operation of the mobile robot and the environmental sensor according to the first embodiment of the present disclosure. FIG. 8 is a flowchart showing another map generation method according to the first embodiment of the present disclosure.

(1) The map generation method of the first aspect according to the present disclosure is a map generation method performed by a first mobile robot that moves in a first region and includes a first sensor and a second sensor, and the first sensor. The first information is acquired from, the first information includes information indicating the movement amount of the first mobile robot, the second information is acquired from the second sensor, and the second information is of the first mobile robot. The third information includes information indicating the distance from the first object existing in the observation area to the first mobile robot, and the third information is acquired from the third sensor installed in the first area, and the third information is the third. The third information including the video information in the observation area of the sensor and indicating the second area which is the detection area of the second sensor calculated based on the first information and the second information is acquired. The fifth information indicating the third region, which is the detection region of the third sensor, calculated based on the information is acquired, and the second region and the third region are obtained based on the fourth information and the fifth information. It is determined whether or not there is a fourth region that overlaps with the region, and if it is determined that the fourth region exists, the fifth region including the first object in the fourth region is said to have the fourth region. 1 The map information of the first area stored in advance in the mobile robot is updated.

With such a configuration, the map information of the mobile robot can be updated in the area where the detection area of the second sensor of the mobile robot and the detection area of the third sensor overlap. Therefore, a map with higher accuracy can be generated.

(2) In the above aspect, further, based on the first information and the second information, the sixth information indicating the current position and posture of the first mobile robot is estimated, and the fourth information is the sixth. It may be calculated informed.

With such a configuration, it is possible to increase the reliability of the map information regarding the area where the detection area of the second sensor of the mobile robot and the detection area of the third sensor overlap. Therefore, a map with higher accuracy can be generated.

(3) In the above aspect, the map information of the first region may be updated by updating the reliability of the first position information indicating the position of the first object.

With such a configuration, it is possible to increase the reliability of the map information regarding the area where the detection area of the second sensor of the mobile robot and the detection area of the third sensor overlap. Therefore, a map with higher accuracy can be generated.

(4) In the above aspect, the reliability of the first position information may be updated by updating the first variance value of the first position information to a second variance value smaller than the first variance value. ..

With such a configuration, it is possible to increase the reliability of the map information regarding the area where the detection area of the second sensor of the mobile robot and the detection area of the third sensor overlap. Therefore, a map with higher accuracy can be generated.

(5) In the above aspect, the third sensor is arranged in the first region, the map information of the first region is represented by the first coordinate system, and the fifth information is the second coordinate system. In addition, the second coordinate system may be converted into the first coordinate system.

With such a configuration, the coordinates of the detection area of the third sensor arranged in the first area can be matched with the coordinates of the map information of the mobile robot moving in the first area, so that a more accurate map can be generated. can do.

(6) In the above aspect, the third sensor is provided in a second mobile robot different from the first mobile robot, and the map information of the first region is represented by the first coordinate system, and the fifth. The information is represented by the second coordinate system of the second mobile robot, and the second coordinate system may be further converted into the first coordinate system.

With such a configuration, since the map information can be generated by using the third sensor of the second mobile robot, it is possible to generate a highly accurate map in a short time.

(7) The map generation method of the second aspect according to the present disclosure is a map generation method performed by a first mobile robot provided with a first sensor and a second sensor by moving in a first region, and the first sensor. The first information is acquired from, the first information includes information indicating the movement amount of the first mobile robot, the second information is acquired from the second sensor, and the second information is of the first mobile robot. The third information includes information indicating the distance from the first object existing in the observation area to the first mobile robot, and the third information is acquired from the third sensor installed in the first area, and the third information is the third. The fourth information indicating the second region, which is the detection region of the second sensor, which includes the video information in the observation region of the sensor and is calculated based on the first information and the second information, is acquired, and the third information is obtained. The fifth information indicating the third region, which is the detection region of the third sensor, calculated based on the above, is acquired, and the fourth information, the fifth information, and the first stored in advance in the first mobile robot are obtained. Based on the map information of the area, it is determined whether or not the second object outside the second area and existing in the fourth area included in the third area has changed from the first position to the second position. When it is determined that the second object has changed from the first position to the second position, the map information of the first area is updated for the fourth area.

With such a configuration, changes in the environment outside the detection region of the second sensor can be detected based on the video information acquired by the third sensor. Therefore, the mobile robot can update the map information about the area where the change in the environment is detected by using the information of the third sensor. As a result, a map with higher accuracy can be generated even when the environment changes.

(8) In the above aspect, further, based on the first information and the second information, the sixth information indicating the current position and posture of the first mobile robot is estimated, and the fourth information is the sixth. It may be calculated informed.

With such a configuration, the mobile robot can robustly estimate its own position and posture, and can generate a map with higher accuracy.

(9) In the above aspect, the map information of the fourth region may be updated by updating the reliability of the first position information indicating the position of the second object.

With such a configuration, the mobile robot can update the reliability of the map information regarding the area where the change in the environment is detected by using the information of the third sensor. As a result, a map with higher accuracy can be generated even when the environment changes.

(10) In the above aspect, the reliability of the first position information may be updated by updating the first variance value of the first position information to a second variance value larger than the first variance value. ..

With such a configuration, it is possible to reduce the reliability of the map information regarding the area where the change in the environment is detected. As a result, the mobile robot can estimate its own position and posture based on the map information of the high-reliability portion without relying on the map information of the low-reliability portion. As a result, a map with higher accuracy can be generated.

(11) In the above aspect, the second dispersion value may be made larger than the first dispersion value according to the amount of change from the first position to the second position.

With such a configuration, the self-position and posture of the mobile robot can be estimated more accurately by increasing the value of the variance in accordance with the amount of change in the environment. This makes it possible to generate more accurate map information.

(12) In the above embodiment, when the current position of the first mobile robot does not exist in the third region and the second region and the third region do not overlap, the first region is the first. The map information of the area may be updated.

With such a configuration, even if the environment changes due to the blind spot of the mobile robot, the reliability of the map information regarding the area where the change in the environment is detected can be updated by using the information acquired by the third sensor. .. Therefore, even when the environment changes due to the blind spot of the mobile robot, the map information of the changed area can be corrected in a short time, and a highly accurate map can be generated.

(13) In the above aspect, the third sensor is arranged in the first region, the map information of the first region is represented by the first coordinate system, and the fifth information is the second coordinate system. In addition, the second coordinate system may be converted into the first coordinate system.

With such a configuration, the coordinates of the detection area of the third sensor arranged in the first area can be matched with the coordinates of the map information of the mobile robot, so that a map with higher accuracy can be generated.

(14) In the above aspect, the third sensor is provided in a second mobile robot different from the first mobile robot, and the map information of the first region is represented by the first coordinate system, and the fifth. The information is represented by the second coordinate system of the second mobile robot, and the second coordinate system may be further converted into the first coordinate system.

With such a configuration, since the map information can be generated by using the third sensor of the second mobile robot, it is possible to generate a highly accurate map in a short time.

(15) In the above aspect, further, with respect to the fifth region in which the second information has not been acquired from the second sensor for a predetermined time, the third dispersion value of the fifth region is obtained with respect to the map information. It may be updated to a fourth variance value greater than the value.

With such a configuration, it is possible to reduce the reliability of the map information relating to the area where the second information is not acquired by the second sensor for a predetermined time. As a result, the self-position and posture can be estimated based on the map information of the high-reliability portion without relying on the map information of the low-reliability portion. As a result, a map with higher accuracy can be generated.

(16) The mobile robot according to the third aspect according to the present disclosure is a mobile robot that moves in a first region, and includes a first sensor that acquires first information indicating the amount of movement of the mobile robot, and the mobile robot. The second sensor that acquires the second information indicating the distance from the first object existing in the observation area to the mobile robot, and (i) the first information and the second sensor calculated based on the second information. The above, which is calculated based on the fourth information indicating the second region which is the detection region of the two sensors and (ii) the third information including the video information in the observation region of the third sensor installed in the first region. Based on the fifth information indicating the third region, which is the detection region of the third sensor, it is determined whether or not there is a fourth region, which is a region where the second region and the third region overlap. When it is determined that the fourth region exists, the map information update for updating the map information of the first region stored in advance in the mobile robot for the fifth region including the first object in the fourth region. It has a part and.

With such a configuration, in the area where the detection area of the second sensor of the mobile robot and the detection area of the third sensor overlap, the map information of the mobile robot can be updated by using the information acquired by the third sensor. it can. Therefore, a map with higher accuracy can be generated.

(17) The mobile robot according to the fourth aspect according to the present disclosure is a mobile robot that moves in a first region, and includes a first sensor that acquires first information indicating the amount of movement of the mobile robot, and the mobile robot. The second sensor that acquires the second information indicating the distance from the first object existing in the observation area to the mobile robot, and (i) the second sensor calculated based on the first information and the second information. The third information calculated based on the fourth information indicating the second region which is the detection region of the sensor and (ii) the third information including the video information in the observation region of the third sensor installed in the first region. Based on the fifth information indicating the third region, which is the detection region of the sensor, and (iii) the map information of the first region stored in advance in the mobile robot, the second region outside the second region. It is determined whether or not the second object existing in the fourth region included in the three regions has changed from the first position to the second position, and the second object has changed from the first position to the second position. When it is determined, the fourth area is provided with a map information updating unit that updates the map information of the first area.

With such a configuration, changes in the environment outside the detection region of the second sensor can be detected based on the third information acquired by the third sensor. Therefore, the mobile robot can update the map information about the area where the change in the environment is detected by using the information of the third sensor. As a result, a map with higher accuracy can be generated even when the environment changes.

(18) The map generation system of the fifth aspect according to the present disclosure is a mobile robot that moves in a first region, and is a first sensor that acquires first information indicating the amount of movement of the mobile robot, and the movement. A mobile robot having a second sensor that acquires a second information indicating a distance from a first object existing in the observation area of the robot to the mobile robot, a third sensor installed in the first area, and the mobile robot. And a server that communicates with the third sensor, the server includes (i) a second region, which is a detection region of the second sensor, calculated based on the first information and the second information. A third region, which is a detection region of the third sensor, calculated based on the fourth information shown and (ii) third information including video information in the observation region of the third sensor installed in the first region. When it is determined whether or not there is a fourth region which is a region where the second region and the third region overlap based on the fifth information indicating the above, and it is determined that the fourth region exists. The fifth region including the first object in the fourth region has a map information updating unit that updates the map information of the first region stored in advance in the mobile robot.

With such a configuration, the map information in the area where the detection area of the second sensor of the mobile robot and the detection area of the third sensor overlap can be updated by using the information acquired by the third sensor. Therefore, a map with higher accuracy can be generated.

(19) The map generation system of the sixth aspect according to the present disclosure is a mobile robot that moves in a first region, and is a first sensor that acquires first information indicating the amount of movement of the mobile robot, and the mobile robot. A mobile robot having a second sensor that acquires a second information indicating the distance from the first object existing in the observation area to the mobile robot, a third sensor installed in the first area, the mobile robot, and the mobile robot. It includes a server that communicates with the third sensor, and the server indicates (i) a second region that is a detection region of the second sensor calculated based on the first information and the second information. A third region indicating a third region, which is a detection region of the third sensor, calculated based on the fourth information and (ii) third information including video information in the observation region of the third sensor installed in the first region. Based on the 5 information and (iii) the map information of the 1st region stored in advance in the mobile robot, a third region outside the 2nd region and existing in the 4th region included in the 3rd region. 2 When it is determined whether or not the object has changed from the first position to the second position and it is determined that the second object has changed from the first position to the second position, the fourth region is described. It has a map information updating unit that updates the map information of the first area.

With such a configuration, changes in the environment outside the detection region of the second sensor can be detected based on the third information acquired by the third sensor. Therefore, the server can update the map information about the area where the change in the environment is detected by using the information of the third sensor. As a result, a map with higher accuracy can be generated even when the environment changes.

(Background to obtain one form related to this disclosure)
In SLAM technology, once highly reliable map information is created, the self-position and posture of the mobile robot are estimated in the area where the map information is created, based exclusively on the information from the external sensor and the created map information. Will be.

In the autonomous driving vehicle disclosed in Patent Document 1, after the map information is generated by the vehicle and the autonomous driving vehicle itself, the object is based on the generated map information and the information obtained by the sensor of the autonomous driving vehicle. It estimates its own position and attitude with respect to.

Patent Document 1 describes that the travelability of an autonomous vehicle is calculated by using the information acquired by the autonomous vehicle and the information from the vehicle. However, in the autonomous driving vehicle disclosed in Patent Document 1, the point of improving the accuracy of map generation by using external sensor information such as an environmental sensor has not been studied.

Further, in the autonomous driving vehicle disclosed in Patent Document 1, when the surrounding environment changes due to a disturbance, the actual map and the map information of the autonomous driving vehicle do not correspond to each other, and the map information of the autonomous driving vehicle and the sensor information. It becomes impossible to estimate the self-position and the posture based on. Further, in the autonomous driving vehicle disclosed in Patent Document 1, it takes time to update the map information regarding the area where the environment has changed so as to correspond to the actual map. These are the issues newly discovered by the inventors.

Therefore, as a result of diligent research, the inventors have found that highly accurate map information can be generated by updating the reliability of the map information of the mobile robot based on the environmental information acquired by the environmental sensor. I found it.

Hereinafter, embodiments of the present disclosure will be described with reference to the accompanying drawings. Further, in each figure, each element is exaggerated for the sake of easy explanation.

(Embodiment 1)
[System configuration]
FIG. 1 shows a schematic configuration diagram of a map generation system according to the first embodiment. As shown in FIG. 1, the map generation system 100 includes a network 110, a mobile robot 200, and environmental sensors 301, 302, and 303.

In the map generation system 100, the mobile robot 200 is connected to a plurality of environment sensors 301, 302, and 303 via the network 110. The environment sensors 301, 302, and 303 are arranged in advance in the surrounding environment at predetermined intervals. The environmental sensors 301, 302, and 303 acquire the environmental information in the detection areas 311, 312, and 313 from above the mobile robot 200, respectively. The detection areas 311, 312, and 313 indicate areas in which the surrounding environment can be observed by the environmental sensors 301, 302, and 303, respectively. The mobile robot 200 acquires the outside world information in the detection area 201 by the outside world sensor described later.

[Mobile robot]
Next, the mobile robot 200 will be described.
The mobile robot 200 has a configuration equivalent to that of a general self-propelled robot. Specifically, it includes a drive device that moves according to movement control information. In addition, the mobile robot 200 has a configuration capable of estimating its own position and posture, communicating with an environmental sensor, and generating map information.

As used herein, the term "location" means a location in map information. Further, the "posture" means the direction of the mobile robot 200, and is expressed by, for example, a rotation angle with respect to a predetermined reference direction. The orientation includes not only the horizontal orientation but also the three-dimensional orientation.

FIG. 2 is a block diagram showing the configuration of the mobile robot 200. As shown in FIG. 2, the mobile robot 200 includes a robot-side communication unit 210, an internal world sensor 220, an external world sensor 230, a coordinate conversion unit 240, a self-position and posture estimation unit 250, a likelihood calculation unit 260, and a map information update unit. It includes 270 and a map information recording unit 280. Further, although the mobile robot 200 includes a control unit that controls these elements, it is omitted in FIG. 2 for the sake of brevity.

<Robot side communication unit>
The robot-side communication unit 210 is a communication device that communicates with the environment sensors 301, 302, and 303. The robot-side communication unit 210 communicates with the environment sensors 301, 302, and 303 via the network 110, and acquires the environment information in the detection areas 311, 312, and 313 of the environment sensors 301, 302, and 303. The robot-side communication unit 210 is accessing the network 110 by wireless communication. The environmental information of the environmental sensors 301, 302, and 303 acquired by the robot-side communication unit 210 is sent to the coordinate conversion unit 240.

<Internal sensor>
The inner world sensor 220 acquires the inner world information of the mobile robot 200. The inside world information is information for predicting the current self-position and posture of the mobile robot 200, and is, for example, information (first information) regarding the amount of movement of the mobile robot 200 and the like. As the internal sensor 220, an acceleration sensor, an angular velocity sensor, a rotary encoder that measures the amount of rotation of the wheel, or the like can be used. The inner world information acquired by the inner world sensor 220 is sent to the self-position and attitude estimation unit 250. The internal sensor 220 may be referred to as a first sensor.

<External sensor>
The outside world sensor 230 acquires the outside world information of the mobile robot 200. The outside world information is information on the actual surrounding environment in the observation area of the outside world sensor 230, for example, information such as the distance between an object (object) arranged in the surrounding environment and the mobile robot 200 (second). Information). As the outside world sensor 230, a camera, an optical distance measuring sensor that measures a distance by a TOF (Time Of Flight) method, or the like can be used. The outside world information acquired by the outside world sensor 230 is sent to the likelihood calculation unit 260. The external sensor 230 may be referred to as a second sensor.

<Coordinate conversion unit>
The coordinate conversion unit 240 receives environmental information from the robot-side communication unit 210. The coordinate conversion unit 240 converts the coordinates of the environmental information so as to match the coordinates of the map information of the mobile robot 200. The conversion to match the coordinates of the environmental information with the coordinates of the map information of the mobile robot 200 is performed by giving the coordinates of the installation positions of the environmental sensors 301, 302, and 303 to the coordinate conversion unit 240 in advance. The environment information whose coordinates have been converted by the coordinate conversion unit 240 is sent to the map information update unit 270.

<Self position and posture estimation unit>
The self-position and posture estimation unit 250 predicts the current self-position and posture of the mobile robot 200 based on the inside world information acquired by the inside world sensor 220. Specifically, the self-position and posture estimation unit 250 uses the information on the movement amount obtained by the internal sensor 220 to provide information on the past position and posture of the mobile robot 200 recorded in the map information recording unit 280. Calculate the current predicted self-position and attitude from. The calculated self-position and attitude information is sent to the likelihood calculation unit 260 and used to calculate the expected outside world information obtained from the self-position and attitude predicted by the self-position and attitude estimation unit 250. .. Further, the self-position and attitude estimation unit 250 receives the likelihood information from the likelihood calculation unit 260. The self-position and posture estimation unit 250 calculates the deviation of the self-position and posture based on the likelihood information and the predicted self-position and posture information, and estimates the current self-position and posture of the mobile robot 200. Information on the self-position and posture estimated by the self-position and posture estimation unit 250 is sent to the map information recording unit 280.

<Likelihood calculation unit>
The likelihood calculation unit 260 calculates the degree of correspondence between the external world information obtained by the external world sensor 230 and the predicted external world information calculated from the self-position and posture predicted by the self-position and posture estimation unit 250, and the likelihood is calculated. To calculate. The likelihood calculation unit 260 calculates the likelihood by using a method of performing a calculation using an image feature amount or an ICP (ITERATION CLOCKEST POINT) method as a point cloud. The likelihood information calculated by the likelihood calculation unit 260 is sent to the self-position and attitude estimation unit 250 and the map information recording unit 280.

<Map information update department>
The map information updating unit 270 determines whether or not there is an area where the detection areas 311, 312, 313 of the environment sensors 301, 302, and 303 overlap with the detection area 201 of the outside world sensor 230. When it is determined that there is an overlapping area, the map information updating unit 270 updates the reliability of the map information of the overlapping area based on the environmental information acquired by the environmental sensors 301, 302, and 303. Specifically, the map information updating unit 270 increases the reliability of the map information regarding the overlapping areas by reducing the value of the variance of the overlapping areas.

"Dispersion" will be described with reference to FIG.
FIG. 3 is a diagram illustrating the definition of variance. As shown in FIG. 3, when the distance from the external sensor 230 mounted on the mobile robot 200 to the object (object) 400 is measured, the measured distance is due to the problem of accuracy due to the resolution of the sensor and the problem of noise. There will be an error. As used herein, the term "variance" means the magnitude of this error. In the present specification, a large variance value indicates a large error and low reliability of map information, and a small variance value indicates a small error and high reliability of map information. ..

Further, the map information updating unit 270 receives coordinate-converted environmental information from the coordinate conversion unit 240, and detects changes in the environment in an area outside the detection area 201 of the external world sensor 230 based on the received environmental information. It has a part. When the change detection unit detects a change in the environment, the map information update unit 270 updates the reliability of the map information regarding the area where the change in the environment is detected. Specifically, the map information updating unit 270 adds the environmental information of the environmental sensors 301, 302, and 303 to the map information of the mobile robot 200 to increase the value of the variance regarding the region where the change in the environment is detected. .. As a result, the map information update unit 270 lowers the reliability of the map information regarding the area where the change in the environment is detected.

The map information updating unit 270 calculates the detection area 201 of the outside world sensor 230 based on the outside world information obtained from the outside world sensor 230. Further, the map information updating unit 270 calculates the detection areas 311, 312, and 313 of the environmental sensors 301, 302, and 303 based on the environmental information obtained from the environmental sensors 301, 302, and 303.
The map information updated by the map information updating unit 270 is sent to the map information recording unit 280.

<Map information recording department>
The map information recording unit 280 includes self-position and attitude information estimated by the self-position and attitude estimation unit 250, likelihood information calculated by the likelihood calculation unit 260, and a map updated by the map information update unit 270. Record the information. Further, the map information recording unit 280 generates map information based on the likelihood information, the outside world information acquired by the outside world sensor 230, and the self-position and attitude information estimated by the self-position and attitude estimation unit 250. And record the generated map information.

Further, the mobile robot 200 includes one or more CPUs, one or more main memories, and one or more auxiliary memories (not shown).

The CPU of the mobile robot 200 described above is variously performed by the coordinate conversion unit 240, the self-position and posture estimation unit 250, the likelihood calculation unit 260, the map information update unit 270, the map information recording unit 280, and the like, which will be described below. Perform arithmetic processing.

The main memory of the mobile robot 200 described above is a storage device that can be directly accessed by the CPU described above, and may be composed of memories such as DRAM, SRAM, flash memory, ReRAM, FeRAM, MRAM, STT-RAM, and PCRAM. ..

The auxiliary storage of the mobile robot 200 described above is a storage device that stores, copies, or backs up the contents of the main storage described above for a long period of time, and may be composed of an HDD, a flash memory, an optical disk, a magnetic disk, or the like.

In the first embodiment, the control unit includes a memory and a processing circuit corresponding to a processor such as a CPU, and includes a coordinate conversion unit 240, a self-position and orientation estimation unit 250, a likelihood calculation unit 260, and a map information update unit 270. The map information recording unit 280 may function these elements by, for example, executing a program stored in the memory to function these elements by the processor. Alternatively, the coordinate conversion unit 240, the self-position and attitude estimation unit 250, the likelihood calculation unit 260, the map information update unit 270, and the map information recording unit 280 may be configured by using an integrated circuit that functions these elements. ..

[Environmental sensor]
Next, the environment sensors 301, 302, and 303 will be described.
FIG. 4 is a block diagram showing the configuration of the environment sensor 301. As shown in FIG. 4, the environment sensor 301 includes an environment information acquisition unit 321 and an environment sensor communication unit 331. Since the environment sensors 302 and 303 have the same configuration as the environment sensor 301, the description thereof will be omitted. The environmental sensors 301, 302, and 303 may be referred to as a third sensor.

<Environmental information acquisition department>
The environmental information acquisition unit 321 acquires the environmental information (third information) in the detection area 311. The environmental information obtained by the environmental information acquisition unit 321 is sent to the environmental sensor communication unit 331. As the environmental information acquisition unit 321, for example, an optical ranging camera is used. The environmental information is, for example, information such as video information by a camera and depth.

<Environmental sensor communication unit>
The environment sensor communication unit 331 communicates with the mobile robot 200, and sends the environment information obtained by the environment information acquisition unit 321 to the mobile robot 200. Specifically, the environment sensor communication unit 331 sends the environment information obtained by the environment information acquisition unit 321 to the robot side communication unit 210 of the mobile robot 200 via the network 110.

[Map information generation method]
A method of generating a map using the mobile robot 200 of the first embodiment will be described.

<High-precision processing of map information>
First, the process of improving the accuracy of the map information will be described with reference to FIGS. 5 and 6.
FIG. 5 shows an example of an operation for improving the accuracy of the map information of the mobile robot 200 as viewed from above. In FIG. 5, the environment sensor 301 is arranged on the wall surface 500, and the environment sensor 301 acquires the environment information (third information) of the inner region (first region) of the wall surface 500. Based on this environmental information, information (fifth information) indicating the detection area (third area) 311 of the environmental sensor 301 is acquired. The mobile robot 200 moves in the inner region of the wall surface 500 and acquires the outside world information by the outside world sensor 230.

As shown in FIG. 5, in the region where the detection region 201 of the external sensor 230 of the mobile robot 200 and the detection region 311 of the environment sensor 301 overlap, the same region is detected by the two sensors. In the first embodiment, in order to improve the accuracy of the map information, the reliability of the map information regarding the overlapping area is updated based on the information obtained by the external world sensor 230 and the information obtained by the environmental sensor 301. There is. Specifically, by adding the information of the environment sensor 301 to the map information generated from the outside world information acquired by the outside world sensor 230 of the mobile robot 200, the reliability of the map information regarding the overlapping area is increased.

FIG. 6 is a flowchart showing a process for improving the accuracy of map information. Hereinafter, the process of improving the accuracy of the map information will be described with reference to FIG. In the process of the first embodiment, EKF (Exted Kalman Filter) is used for estimating the self-position and posture of the mobile robot 200 and creating a map. Also, as the reliability, the reciprocal of the covariance value of the landmark in the area corresponding to the coordinates of the map information is used.

As shown in FIG. 6, in step ST101, the self-position and posture of the mobile robot 200 are predicted by using the information (first information) regarding the movement amount obtained by the internal sensor 220. Specifically, the self-position and posture estimation unit 250 calculates the current self-position and posture from the information on the movement amount and the past self-position and posture recorded in the map information recording unit 280.

In step ST102, the likelihood is based on the predicted outside world information obtained from the self-position and posture information predicted by the self-position and posture estimation unit 250 and the outside world information (second information) obtained from the outside world sensor 230. Calculate the degree. Specifically, the likelihood calculation unit 260 calculates the expected outside world information obtained by the self-position and posture predicted in step ST101. Then, the likelihood calculation unit 260 calculates the likelihood by calculating the degree of correspondence between the predicted outside world information and the outside world information actually obtained from the outside world sensor 230.

In step ST103, the current self-position and posture of the mobile robot 200 are estimated based on the likelihood information obtained in step ST102 and the self-position and posture information predicted in step ST101. Specifically, the self-position and posture estimation unit 250 calculates the deviation of the self-position and posture based on the likelihood information and the self-position and posture information predicted in step ST101, and calculates the current self-position and posture. presume.

In step ST104, map information is generated from the current self-position and posture information of the mobile robot 200 obtained in step ST103 and the outside world information. The generated map information is recorded in the map information recording unit 280.

In step ST105, the detection region (second region) 201 of the external world sensor 230 of the mobile robot 200 is calculated from the current self-position and posture information (sixth information) of the mobile robot 200 obtained in step ST103. As a result, information (fourth information) indicating the detection area 201 of the external world sensor 230 of the mobile robot is acquired.

In step ST106, the detection area (third information) is based on the information of the detection area 201 of the external sensor 230 (fourth information) obtained in step ST105 and the information of the detection area 311 of the environment sensor 301 (fifth information). It is determined whether or not there is an overlapping region (fourth region) between the two regions) 201 and the detection region (third region) 311. In step ST106, the coordinate conversion unit 240 converts the coordinates of the environment information (second coordinate system) obtained by the environment sensor 301 so as to match the coordinates of the map information of the mobile robot 200 (first coordinate system). .. Then, the detection area 311 of the environment sensor 301 is calculated from the coordinate-converted environment information.

If it is determined in step ST106 that there is an overlapping region (fourth region), the process shifts to step ST107. If it is determined in step ST106 that there is no overlapping area, the process ends.

In step ST107, the reliability of the map information of the mobile robot 200 is updated by using the information of the environment sensor 301. Specifically, the map information update unit 270 adds the environmental information of the environmental sensor 301 to reduce the value of the dispersion of the map information regarding the area including the object (fifth area) among the overlapping areas, and the map information. Increase the reliability of. For example, the map information updating unit 270 updates the map information of the inner region of the wall surface 500 by updating the reliability of the position information indicating the position of the object in the overlapping region. The updated map information is recorded in the map information recording unit 280.

In the map generation method according to the first embodiment, the map information is highly accurate by performing the above processing. The above description describes a case where the detection area 311 of one environment sensor 301 and the detection area 201 of the outside world sensor 230 of the mobile robot 200 overlap. When the detection areas of the plurality of environmental sensors and the detection areas 201 of the external sensor 230 of the mobile robot 200 overlap, step ST107 is executed for all the environmental sensors determined to have overlapping detection areas.

[Map information update processing when a disturbance occurs]
Next, in the surrounding environment, the update process of the map information when the environment changes due to the disturbance outside the detection area 201 of the external sensor 230 of the mobile robot 200 will be described with reference to FIGS. 7A, 7B, and 8. ..

7A and 7B show an example of the operation of updating the map information of the mobile robot 200 when the environment changes, as viewed from above. In FIGS. 7A and 7B, the environment sensor 301 is arranged on the wall surface 500, and the environment sensor 301 acquires the environment information (third information) of the inner region (first region) of the wall surface 500. Based on this environmental information, information (fifth information) indicating the detection area (third area) 311 of the environmental sensor 301 is acquired. The mobile robot 200 moves in the inner region of the wall surface 500 and acquires the outside world information by the outside world sensor 230.

As shown in FIG. 7A, when the object (object) 400 moves in the direction of the white arrow outside the detection area (second area) 201 of the external sensor 230 of the mobile robot 200, the change detection unit of the map information update unit 270. However, the moved region of the object 400 is detected as the region 401 in which the environment has changed. In the detected area 401, the map information recorded in the mobile robot 200 will be different from the actual map and will not correspond. Therefore, even if the mobile robot 200 tries to estimate the self-position and the posture based on the map information recorded by itself and the information obtained by the external world sensor 230, the self-position and the posture cannot be estimated correctly. Therefore, in the first embodiment, a process is performed in which the value of the dispersion of the map information regarding the region 401 in which the change in the environment is detected is increased and the reliability of the map information is lowered.

As shown in FIG. 7B, when the outside world sensor 230 of the mobile robot 200 acquires the outside world information of the area 401 that has detected the change in the environment, the reliability of the map information of the area 401 is lowered. Therefore, the mobile robot 200 estimates its own position and posture based on the map information of the highly reliable portion other than the region 401 in which the change in the environment is detected. Further, the area 401 in which the change in the environment is detected can be updated to highly reliable map information by the above-mentioned high-precision processing of the map information.

FIG. 8 is a flowchart showing a map information update process when the environment changes due to a disturbance. Hereinafter, using FIG. 8, the map information update process will be described when the environment changes due to disturbance outside the detection area 201 of the external sensor 230 of the mobile robot 200.

As shown in FIG. 8, in step ST201, the current self-position and posture of the mobile robot 200 are read out. Specifically, the information on the current self-position and posture of the mobile robot 200 recorded in the map information recording unit 280 is read out. The current self-position and posture of the mobile robot 200 in step ST201 are the self-position and posture estimated in step ST103 shown in FIG. 6 above. Note that step ST201 may be replaced with steps ST101 to ST104 of FIG. 6 described above.

In step ST202, the detection area (second area) 201 of the external world sensor 230 of the mobile robot 200 is calculated from the current self-position and posture information (sixth information) of the mobile robot 200 read in step ST201. As a result, information (fourth information) indicating the detection area 201 of the external world sensor 230 of the mobile robot is acquired.

In step ST203, the change detection unit of the map information update unit 270 detects a change in the environment based on the information (fifth information) indicating the detection area (third area) 311 of the environment sensor 301. Specifically, the change detection unit makes an object in the detection area 311 of the environment sensor 301 based on the information (fifth information) indicating the detection area (third area) 311 of the environment sensor 301 and the past map information. It detects whether or not the surrounding environment has changed due to a disturbance such as the movement of the 400. Further, in step ST203, the region 401 in which the change in the environment is detected is detected. In step ST203, when a change in the environment is detected, the process proceeds to step ST204, and when no change in the environment is detected, the process ends.

In step ST204, it is detected whether or not the mobile robot 200 exists in the detection area 311 of the environment sensor 301. Specifically, the information on the current self-position of the mobile robot 200 is read from the map information recording unit 280, and it is determined whether or not the mobile robot 200 is located in the detection area 311 of the environment sensor 301. In step ST204, if the mobile robot 200 does not exist in the detection area 311 of the environment sensor 301, the process shifts to step ST205. When the mobile robot 200 exists in the detection area 311 of the environment sensor 301, the process ends.

In step ST205, the detection area (third information) is based on the information of the detection area 201 of the external sensor 230 (fourth information) obtained in step ST202 and the information of the detection area 311 of the environment sensor 301 (fifth information). It is determined whether or not there is an overlapping region (fourth region) between the two regions) 201 and the detection region (third region) 311. In step ST205, if it is determined that there is no overlapping area, the process proceeds to step ST206, and if it is determined that there is an overlapping area, the process ends.

In step ST206, it is determined whether or not there is map information regarding the area 401 in which the change in the environment is detected. Specifically, it is determined whether or not the map information recording unit 280 has recorded the map information regarding the area 401 in which the change in the environment is detected. In step ST206, if there is map information about the area 401 in which the change in the environment is detected, the process shifts to step ST207. If there is no map information about the area 401 that detected the change in the environment, the process ends.

In step ST207, the reliability of the map information regarding the region 401 in which the change in the environment is detected is updated by using the information of the environment sensor 301. Specifically, the map information updating unit 270 increases the value of the dispersion of the map information regarding the area 401 that has detected the change in the environment, and lowers the reliability of the map information regarding the area 401 that has detected the change in the environment. For example, when the map information updating unit 270 determines that the object in the overlapping area has changed from the first position to the second position, the map information updating unit 270 updates the reliability of the map information in the overlapping area to update the reliability of the map information in the overlapping area, thereby forming the inner area of the wall surface 500. Update map information. The map information update unit 270 increases the value of the variance according to the amount of change in the environment detected by the environment sensor 301.

In the map generation method according to the first embodiment, by performing the above processing, it is possible to reflect the change in the environment due to the disturbance generated in the area that cannot be directly observed by the external sensor 230 of the mobile robot 200 in the map information. It becomes.

[Other map update processing]
In the map generation method according to the first embodiment, in the map information once generated, the value of the dispersion of the map information regarding the area where the outside world sensor 230 of the mobile robot 200 has not acquired the outside world information for a predetermined time is increased. To do. After the map information is generated, there is a possibility that the environment has changed in the area where the outside world information has not been acquired for a predetermined time. Therefore, in the map generation method according to the first embodiment, when the outside world information is not acquired by the outside world sensor 230 for a predetermined time for the once generated map information, the value of the dispersion of the map information regarding the area is increased. , The reliability of map information is lowered. The predetermined time can be arbitrarily determined depending on conditions such as the size of the area for generating the map information and the moving speed of the mobile robot 200.

[effect]
According to the map generation method and the mobile robot 200 according to the first embodiment, the following effects can be obtained.

The map generation method and the mobile robot 200 according to the first embodiment reduce the value of the distribution of the map information regarding the area where the detection area 201 of the external sensor 230 of the mobile robot 200 and the detection area 311 of the environment sensor 301 overlap. , The reliability of map information is increasing. As described above, in the first embodiment, the map information can be generated with high accuracy by creating the map information by combining the information acquired by the external sensor 230 of the mobile robot 200 and the information acquired by the environment sensor 301. it can.

According to the first embodiment, the reliability of the map information regarding the area 401 is reduced by lowering the value of the dispersion of the map information about the area 401 where the change in the environment is detected outside the detection area 201 of the external sensor 230 of the mobile robot 200. Is lowered. Therefore, the mobile robot 200 can estimate its own position and posture by using the map information of the highly reliable portion without using the map information of the unreliable portion where the environment has changed. .. As described above, the map generation method and the mobile robot 200 of the first embodiment can robustly estimate the self-position and the posture of the mobile robot 200 even when the environment is changed due to the disturbance. Therefore, even if the environment changes due to the disturbance, the map generation method and the mobile robot 200 of the first embodiment can correct the map information of the area where the environment change has occurred and generate the map information with high accuracy. .. Further, in the area 401 where the change in the environment is detected, the highly accurate map information can be reconstructed in a short time by the outside world sensor 230 and the environment sensor 301 of the mobile robot 200.

Further, the self-position and posture of the mobile robot 200 can be estimated more accurately by increasing the value of the dispersion of the map information regarding the region 401 in which the change in the environment is detected according to the amount of the change in the environment.

According to the first embodiment, when the change in the environment is detected, the change in the environment is detected when the detection area 201 of the external sensor 230 of the mobile robot 200 and the detection area 311 of the environment sensor 301 do not overlap. The reliability of the map information related to the created area 401 is updated. Therefore, the change in the environment caused by the blind spot of the mobile robot 200 can be detected, and the area where the change in the environment has occurred can be reflected in the map information of the mobile robot 200.

According to the first embodiment, in the area where the outside world information is not acquired by the outside world sensor 230 for a predetermined time after the map information is generated once, in consideration of the possibility that the environment has changed, the environment may be changed. The value of the variance is increased and the reliability of the map information about the area is decreased. Therefore, in the map generation method and the mobile robot 200 of the first embodiment, the self-position and the posture of the mobile robot 200 can be robustly estimated.

In the first embodiment, the configuration in which the mobile robot 200 and the environmental sensors 301, 302, and 303 communicate with each other via the network 110 has been described, but the present invention is not limited to this. For example, the system may be configured to include a server that communicates with the mobile robot 200 and the environmental sensors 301, 302, and 303 via the network 110. In such a system configuration, the processing of each step shown in FIGS. 6 and 8 may be executed on the server side. That is, the server may include a self-position and attitude estimation unit 250 and a map information update unit 270. For example, the server acquires the environmental information obtained from the environmental sensors 301, 302, and 303, and the external world information and the internal world information acquired from the mobile robot 200 via the network. Then, the server may perform high-precision processing of the map information or update processing of the map information when a disturbance occurs, based on the acquired information.

In the first embodiment, an example in which the change detection unit of the map information update unit 270 detects a change in the environment based on the environmental information of the environment sensor 301 has been described, but the present invention is not limited to this. For example, environmental sensors 301, 302, and 303 may be used to detect changes in the environment.

In the first embodiment, the accuracy of the map information is improved based on the environmental information obtained from the environmental sensors 301, 302, and 303, but the accuracy is not limited to this. For example, when the distance measuring sensor is used as the environment sensors 301, 302, 303, the accuracy of the self-position and posture information of the mobile robot 200 is improved by performing the likelihood calculation process on the self-position and posture information. be able to.

In the first embodiment, the coordinate conversion unit 240 converts the coordinates of the environmental information into the coordinates of the map information of the mobile robot 200 by acquiring the installation positions of the environmental sensors 301, 302, and 303 in advance. , Not limited to this. For example, the environment sensors 301, 302, and 303 capture the mobile robot 200, and at that time, the conversion parameters are set based on the position information estimated by the self-position and posture estimation unit 250 and the coordinates captured by the environment sensors 301, 302, 303. You may estimate. For example, in the case of the mobile robot 200 that moves in a two-dimensional plane, the coordinate conversion unit 240 can convert the environment information into the coordinates of the map information of the mobile robot 200 by projective conversion.

In the first embodiment, an example in which the environment sensors 301, 302, and 303 are fixedly arranged in the surrounding environment at predetermined intervals has been described, but the present invention is not limited thereto. For example, the environmental sensor may be a sensor whose detection area can be changed, such as a swing-type sensor that changes the installation angle according to time. An environmental sensor whose detection area can be changed can acquire a wider range of environmental information. Further, in the case of the hanging type sensor, the coordinates of the environmental information can be converted into the coordinates of the map information of the mobile robot 200 by notifying the coordinate conversion unit 240 of the installation angle at the time of acquiring the environmental information.

In the first embodiment, the configuration in which the inner world sensor 220 and the outer world sensor 230 each include one is described, but the present invention is not limited thereto. The inner world sensor 220 and the outer world sensor 230 may be provided with at least one or more of each. By using the plurality of internal world sensors 220 and the plurality of external world sensors 230, more internal world information and external world information can be acquired, so that the self-position and posture of the mobile robot 200 can be estimated with higher accuracy. it can.

In the first embodiment, the acceleration sensor and the angular velocity sensor have been described as the internal sensor 220, but the present invention is not limited to this. The internal sensor 220 may be, for example, a magnetic field sensor, a visual odometry using a camera, or the like.

In the first embodiment, the configuration using the three environmental sensors 301, 302, and 303 has been described, but at least one environmental sensor may be provided. The number of environmental sensors may be determined by various conditions such as an area for generating map information and the complexity of the surrounding environment. By using a plurality of environmental sensors, more environmental information can be acquired, so that more accurate map information can be generated.

In the first embodiment, the generated map information may be two-dimensional map information or three-dimensional map information. The map information means information having both the coordinates of the obstacle position and the amount of dispersion in each axial direction. The map information can be visually represented by, for example, a grid map, a line diagram, a point diagram, or the like.

In the first embodiment, an example in which one mobile robot 200 generates a map has been described, but at least one mobile robot may be provided. When a plurality of mobile robots are used, highly accurate map information can be generated in a short time.

Further, when a plurality of mobile robots are used, the external world sensor 230 mounted on each mobile robot can also be used as an environmental sensor. Therefore, the outside world information acquired by the outside world sensor 230 of each mobile robot can be used for estimating the self-position and the posture, and can also be used as the environment information of the surrounding environment. With such a configuration, highly accurate map information can be generated in a shorter time.

Sharing and processing map information by multiple robots makes it possible to update a wide range of maps with high frequency. Therefore, when a plurality of robots are used, it is useful for, for example, monitoring work. Further, it is possible to perform high-precision processing of the map information shown in FIG. 6 and update processing of the map information when a disturbance shown in FIG. 8 occurs in a region that cannot be observed by the environmental sensor whose position is fixed. Therefore, when a plurality of robots are used, it is possible to improve the accuracy of the map information in the blind spot area of the environmental sensor.

The map generation method of the first embodiment has described the process of not giving the map information to the mobile robot 200 in advance, but the method is not limited to this. For example, the process may be a process in which map information is given to the mobile robot 200 in advance and the map information is updated.

Although each process shown in FIGS. 6 and 8 has been described in detail in the first embodiment, the present disclosure is not limited to these processes. The processes shown in FIGS. 6 and 8 are examples, and some processes may be omitted or known processes may be added.

In the first embodiment, an example in which the processing is terminated when it is determined in step ST205 that there is an overlapping region has been described, but the present invention is not limited to this. For example, in step ST205, the above-mentioned high-precision map information processing may be performed on the overlapping regions.

Although the present disclosure has been fully described in connection with preferred embodiments with reference to the accompanying drawings, various modifications and modifications are obvious to those skilled in the art. It should be understood that such modifications and amendments are included within the scope of the present disclosure by the appended claims. For example, the mobile robot may be a vehicle, and the environmental sensor may be a surveillance camera. Further, the external world sensor and the environment sensor may be LRF (Laser Range Finder), LIDAR (Laser Imaging Detection and Ranger), a camera, a depth camera, a stereo camera, RADAR, and TOF (Time of Flight).

The present disclosure is useful as position recognition of an autonomously moving robot in an environment with a lot of disturbance. The present disclosure is also useful when applied to infrastructure inspections and robots for ocean exploration that move in an environment with many obstacles, and to create a map at the same time as position recognition.

100 Map generation system 110 Network 200 Mobile robot 201 Detection area 210 Robot side communication unit 220 Internal sensor 230 External sensor 240 Coordinate conversion unit 250 Self-position and posture estimation unit 260 Probability calculation unit 270 Map information update unit 280 Map information recording unit 301, 302, 303 Environmental sensor 311, 312, 313 Detection area 321 Environmental information acquisition unit 331 Environmental sensor communication unit 400 Object 401 Area 500 Wall surface

Claims (19)

A map generation method performed by a first mobile robot equipped with a first sensor and a second sensor that moves in a first area.
The first information is acquired from the first sensor, and the first information includes information indicating the amount of movement of the first mobile robot.
The second information is acquired from the second sensor, and the second information includes information indicating the distance from the first object existing in the observation area of the first mobile robot to the first mobile robot.
The third information is acquired from the third sensor installed in the first region, and the third information includes the video information in the observation region of the third sensor.
The fourth information indicating the second region, which is the detection region of the second sensor, calculated based on the first information and the second information, is acquired.
Acquiring the fifth information indicating the third region, which is the detection region of the third sensor, calculated based on the third information,
Based on the 4th information and the 5th information, it is determined whether or not there is a 4th region which is a region where the 2nd region and the 3rd region overlap.
When it is determined that the fourth region exists, the map information of the first region stored in advance in the first mobile robot is updated for the fifth region including the first object in the fourth region.
Map generation method. further,
Based on the first information and the second information, the sixth information indicating the current position and posture of the first mobile robot is estimated, and the sixth information is estimated.
The fourth information is calculated based on the sixth information.
The map generation method according to claim 1. By updating the reliability of the first position information indicating the position of the first object, the map information of the first area is updated.
The map generation method according to claim 1. By updating the first variance value of the first position information to a second variance value smaller than the first variance value, the reliability of the first position information is updated.
The map generation method according to claim 3. The third sensor is arranged in the first region.
The map information of the first region is represented by the first coordinate system.
The fifth information is represented by the second coordinate system.
further,
Converting the second coordinate system to the first coordinate system,
The map generation method according to claim 1. The third sensor is provided in a second mobile robot different from the first mobile robot.
The map information of the first region is represented by the first coordinate system.
The fifth information is represented by the second coordinate system of the second mobile robot.
further,
Converting the second coordinate system to the first coordinate system,
The map generation method according to claim 1. A map generation method performed by a first mobile robot equipped with a first sensor and a second sensor that moves in a first area.
The first information is acquired from the first sensor, and the first information includes information indicating the amount of movement of the first mobile robot.
The second information is acquired from the second sensor, and the second information includes information indicating the distance from the first object existing in the observation area of the first mobile robot to the first mobile robot.
The third information is acquired from the third sensor installed in the first region, and the third information includes the video information in the observation region of the third sensor.
The fourth information indicating the second region, which is the detection region of the second sensor, calculated based on the first information and the second information, is acquired.
The fifth information indicating the third region which is the detection region of the third sensor calculated based on the three information is acquired, and the fifth information is acquired.
Based on the fourth information, the fifth information, and the map information of the first region stored in advance in the first mobile robot, the fourth region outside the second region and included in the third region Judging whether the existing second object has changed from the first position to the second position,
When it is determined that the second object has changed from the first position to the second position, the map information of the first area is updated for the fourth area.
Map generation method. further,
Based on the first information and the second information, the sixth information indicating the current position and posture of the first mobile robot is estimated, and the sixth information is estimated.
The fourth information is calculated based on the sixth information.
The map generation method according to claim 7. By updating the reliability of the first position information indicating the position of the second object, the map information of the fourth area is updated.
The map generation method according to claim 7. By updating the first variance value of the first position information to a second variance value larger than the first variance value, the reliability of the first position information is updated.
The map generation method according to claim 9. The second dispersion value is made larger than the first dispersion value according to the amount of change from the first position to the second position.
The map generation method according to claim 10. When the current position of the first mobile robot does not exist in the third region and the second region and the third region do not overlap, the map information of the first region is updated for the fourth region. ,
The map generation method according to claim 8. The third sensor is arranged in the first region.
The map information of the first region is represented by the first coordinate system.
The fifth information is represented by the second coordinate system.
further,
Converting the second coordinate system to the first coordinate system,
The map generation method according to claim 7. The third sensor is provided in a second mobile robot different from the first mobile robot.
The map information of the first region is represented by the first coordinate system.
The fifth information is represented by the second coordinate system of the second mobile robot.
further,
Converting the second coordinate system to the first coordinate system,
The map generation method according to claim 7. further,
Regarding the fifth region in which the second information has not been acquired from the second sensor for a predetermined time, the third variance value of the fifth region is updated to a fourth variance value larger than the third variance value for the map information. To do,
The map generation method according to claim 10. A mobile robot that moves in the first area
A first sensor that acquires first information indicating the amount of movement of the mobile robot, and
A second sensor that acquires second information indicating the distance from the first object existing in the observation area of the mobile robot to the mobile robot, and
(I) The fourth information indicating the second region, which is the detection region of the second sensor, calculated based on the first information and the second information, and (ii) the second information installed in the first region. The second region and the second region are calculated based on the fifth information indicating the third region, which is the detection region of the third sensor, calculated based on the third information including the video information in the observation region of the three sensors. It is determined whether or not there is a fourth region that overlaps with the three regions, and if it is determined that the fourth region exists, the fifth region including the first object in the fourth region A map information update unit that updates the map information of the first area stored in advance in the mobile robot, and a map information update unit.
A mobile robot equipped with. A mobile robot that moves in the first area
A first sensor that acquires first information indicating the amount of movement of the mobile robot, and
A second sensor that acquires second information indicating the distance from the first object existing in the observation area of the mobile robot to the mobile robot, and
(I) The first information, the fourth information indicating the second region which is the detection region of the second sensor calculated based on the first information, and (ii) the third information installed in the first region. The fifth information indicating the third region, which is the detection region of the third sensor, calculated based on the third information including the video information in the observation region of the sensor, and (iii) the third information stored in advance in the mobile robot. Based on the map information of one region, whether or not the second object outside the second region and existing in the fourth region included in the third region has changed from the first position to the second position. When it is determined that the second object has changed from the first position to the second position, the map information updating unit that updates the map information of the first area for the fourth area
A mobile robot equipped with. A mobile robot that moves in a first region, a first sensor that acquires first information indicating the amount of movement of the mobile robot, and a distance from a first object existing in the observation region of the mobile robot to the mobile robot. A mobile robot having a second sensor that acquires the second information indicating
With the third sensor installed in the first area,
A server that communicates with the mobile robot and the third sensor,
With
The server
(I) The fourth information indicating the second region, which is the detection region of the second sensor, calculated based on the first information and the second information, and (ii) the second information installed in the first region. The second region and the second region are calculated based on the fifth information indicating the third region, which is the detection region of the third sensor, calculated based on the third information including the video information in the observation region of the three sensors. It is determined whether or not there is a fourth region that overlaps with the three regions, and if it is determined that the fourth region exists, the fifth region including the first object in the fourth region A map information update unit that updates the map information of the first area stored in advance in the mobile robot, and a map information update unit.
Has a map generation system. A mobile robot that moves in a first region, a first sensor that acquires first information indicating the amount of movement of the mobile robot, and a distance from a first object existing in the observation region of the mobile robot to the mobile robot. A mobile robot having a second sensor that acquires the second information indicating
With the third sensor installed in the first area,
A server that communicates with the mobile robot and the third sensor,
With
The server
(I) The first information, the fourth information indicating the second region which is the detection region of the second sensor calculated based on the first information, and (ii) the third information installed in the first region. The fifth information indicating the third region, which is the detection region of the third sensor, calculated based on the third information including the video information in the observation region of the sensor, and (iii) the third information stored in advance in the mobile robot. Based on the map information of one region, whether or not the second object outside the second region and existing in the fourth region included in the third region has changed from the first position to the second position. When it is determined that the second object has changed from the first position to the second position, the map information update unit that updates the map information of the first area for the fourth area,
Has a map generation system.

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